Quick start

Step 1: upload data to katiML

Python

import os
os.environ['DIOPTRA_API_KEY'] = 'my_api_key'

from dioptra.lake.utils import upload_to_lake, wait_for_upload

upload_id = upload_to_lake(records=[{
    'image_metadata': {
        'uri': 'https://dioptra-demo.s3.us-east-2.amazonaws.com/stanford-dogs-dataset/n02085620-Chihuahua/n02085620_8578.jpg'
    },
    'groundtruth': {
        'task_type': 'CLASSIFICATION',
        'class_name': 'chihuahua'
    },
    'tags': {
        'source': 'stanford_dogs'
    }}])

wait_for_upload(upload_id)

Step 2: check your data in the UI

Step 3: query katiML

Query like a SQL database, get it as a DataFrame

Python

import os
os.environ['DIOPTRA_API_KEY'] = 'my_api_key'

from dioptra.lake.utils import select_datapoints

select_datapoints(
    filters=[{
        'left': 'tags.value',
        'op': '=',
        'right': 'stanford_dogs'}])